calculateSimilarity returns a similarity score between 0.0 and 1.0. Substring containment scores 0.7-1.0; otherwise Levenshtein distance is used.
(query, target string)
| 279 | // calculateSimilarity returns a similarity score between 0.0 and 1.0. |
| 280 | // Substring containment scores 0.7-1.0; otherwise Levenshtein distance is used. |
| 281 | func calculateSimilarity(query, target string) float64 { |
| 282 | lowerQuery := strings.ToLower(query) |
| 283 | lowerTarget := strings.ToLower(target) |
| 284 | |
| 285 | if lowerQuery == lowerTarget { |
| 286 | return 1.0 |
| 287 | } |
| 288 | if strings.Contains(lowerTarget, lowerQuery) { |
| 289 | return 0.7 + 0.3*float64(len(lowerQuery))/float64(len(lowerTarget)) |
| 290 | } |
| 291 | |
| 292 | maxLen := len(lowerQuery) |
| 293 | if len(lowerTarget) > maxLen { |
| 294 | maxLen = len(lowerTarget) |
| 295 | } |
| 296 | if maxLen == 0 { |
| 297 | return 1.0 |
| 298 | } |
| 299 | |
| 300 | dist := levenshtein(lowerQuery, lowerTarget) |
| 301 | return 1.0 - float64(dist)/float64(maxLen) |
| 302 | } |
| 303 | |
| 304 | // levenshtein computes the edit distance between two strings. |
| 305 | func levenshtein(a, b string) int { |